Advertisement
Published in:
2015 | OriginalPaper | Chapter
Texture-Based Continuous Probabilistic Framework for Robust Medical Image Representation and Classification
Author : Dror Lederman
Published in: 6th European Conference of the International Federation for Medical and Biological Engineering
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
This paper presents a texture-based continuous probabilistic framework for robust image representation. According to the proposed approach, images taken at different angles are represented using several probabilistic models connected in parallel. The classification decision is made based on a maximum likelihood approach, which is insensitive to the angle at which the image was taken. The proposed approach is evaluated using a dataset of 100 images that includes three classes of anatomical structures of the upper airways. The results show that the approach can be used to efficiently and reliably represent and classify medical images acquired during various procedures.